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Basic Linear Geostatistics, by Margaret Armstrong
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Based on a postgraduate course that has been successfully taught for over 15 years, the underlying philosophy here is to give students an in-depth understanding of the relevant theory and how to put it into practice. This involves going into the theory in more detail than most books do, and also discussing its applications. It is assumed that readers, students and professionals alike are familiar with basic probability and statistics, as well as the matrix algebra needed for solving linear systems; however, some reminders on these are given in an appendix. Exercises are integrated throughout, and the appendix contains a review of the material.
- Sales Rank: #1627430 in Books
- Brand: Brand: Springer
- Published on: 2013-10-04
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .39" w x 6.10" l, .60 pounds
- Binding: Paperback
- 155 pages
- Used Book in Good Condition
Most helpful customer reviews
1 of 1 people found the following review helpful.
Five Stars
By Stephen Hancock
A surprisingly clear and lucid account that covers all of the essentials in a sometimes opaque subject.
1 of 2 people found the following review helpful.
Good text but there is not pictures enough
By TONATIUH SUAREZ
It is a very good text book for bachelor degree level, but, the book could be better if the pictures were designed again with powered tools. There is very good examples, but a primitive picture make it look not so good.
2 of 2 people found the following review helpful.
Good basic text for the practicioner
By Engineer Always Learning
This text explains in plain english, in a quite readable way, the basics of basic geostatistics. By basics I mean some background statistical theory (stationarity, inherent hypothesis), covariances, variograms, simple kriging and ordinary kriging. The book does not cover universal kriging, disjunctive kriging, indicator kriging, etc. The book is clearly focused on engineers for the mining industry as all of the terminology comes from mining as do all of the examples. Not being in the mining industry I found following some of the examples difficult due to not understanding mining terminology.
While the preface indicates this text is intended for a postgraduate course, I find this hard to believe. The level of the mathematics and the text seems more appropriate for an undergraduate course. Where the text excels is in accompanying each new element of the theory with concrete examples on real data. The reader can work the examples and see what the theory means. A lot of the geostatistics journal literature presupposes that you've read something like this text and have digested it.
The text contain typos in some of its equations - generally easy to spot, but annoying none the less. It seems clear that this text didn't get much in the way of editorial guidance or review. And in some instances, it appears a technical review should have been done. In one example from section 2.4, Armstrong ascribes to stationarity "This makes statistical inference possible on a single realization" what should be ascribed to ergodicity.
For more theoretical and more comprehensive coverage, the texts by Cressie (Statistics for Spatial Data) or by Chiles and Delfiner (Geostatistics: Modeling Spatial Uncertainty) are quite good. I give this four stars because it's a very readable text for learning the basics and clearing up stuff left unstated or assumed known when you first read something like Cressie's text (I read that first) and it's examples are extremely helpful in understanding - too few textbooks use such examples when attempting to teach basic theory.
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